How to monitor transformers in smart grid

With the continuous growth of power demand and the continuous optimization of energy structure, smart grid, as an important development direction of modern power system, is gradually replacing traditional power grid. In smart grid, transformer is one of the core devices of power transmission and distribution, and its running state directly affects the safety and stability of the whole grid. Therefore, how to effectively monitor the transformers in the smart grid has become an important issue to ensure the reliable operation of the grid.

The traditional transformer monitoring method mainly relies on regular inspection and manual data analysis, which has some problems such as delayed response, low efficiency and delayed information. The smart grid realizes real-time, remote and intelligent monitoring of transformers by integrating advanced sensing technology, communication technology and data analysis technology.

The monitoring of transformers in smart grid is mainly realized through the following aspects:

First, the application of sensor technology. Various types of sensors, such as temperature sensor, oil level sensor, gas sensor and vibration sensor, are installed in and around the transformer, which can collect various parameters of the transformer in real time. For example, by detecting the dissolved gas content in the insulating oil inside the transformer, it can be judged whether there is partial discharge or overheating; Monitoring the temperature change of winding by temperature sensor is helpful to prevent equipment damage caused by overheating.

Secondly, the support of communication network. Using wireless communication technology (such as 5G, optical fiber, LoRa, etc.) to transmit the data collected by sensors to the control center or cloud platform in real time, so that the operation and maintenance personnel can grasp the running status of the transformer at any time. This remote monitoring method not only improves the monitoring efficiency, but also reduces the cost and risk of manual inspection.

Third, the analytical ability of big data and artificial intelligence. By analyzing and processing a large number of historical data and real-time data, the intelligent system can identify the trend and abnormal mode of equipment operation. For example, based on machine learning algorithm, possible faults of transformers can be predicted and early warning can be given, so as to realize the transition from "fault maintenance" to "predictive maintenance" and improve the availability of equipment and the reliability of power grid operation.

In addition, the intelligent monitoring system can be linked with the intelligent dispatching system to automatically adjust the operation strategy when the transformer load is too high or abnormal, so as to ensure the continuity of power supply.

In a word, transformer monitoring in smart grid has changed from traditional passive management to intelligent management process integrating perception, communication and analysis. This not only improves the safety and efficiency of the power system, but also lays the foundation for building a greener and more efficient energy system. In the future, with the further development of new technologies such as Internet of Things and edge computing, the transformer monitoring system will be more accurate and intelligent, which will inject new impetus into the development of the power industry.